DocumentCode :
1659931
Title :
Extension of rough set under incomplete information systems
Author :
Wang, Guoyin
Author_Institution :
Inst. of Comput. Sci. & Technol., Chongqing Univ. of Posts & Telecommun., China
Volume :
2
fYear :
2002
fDate :
6/24/1905 12:00:00 AM
Firstpage :
1098
Lastpage :
1103
Abstract :
The classical rough set theory is based on complete information systems. It classifies objects using upper-approximation and lower-approximation defined on an indiscernibility relation that is a kind of equivalent relation. In order to process incomplete information systems, the classical rough set theory needs to be extended, especially, the indiscernibility relation needs to be extended to some inequivalent relation. There are several extensions for the indiscernibility relation at present, such as tolerance relation, non-symmetric similarity relation, and valued tolerance relation. Unfortunately, these extensions have their own limitation. We develop a new extension of rough set theory that is based on a limited tolerance relation
Keywords :
information systems; knowledge acquisition; probability; rough set theory; incomplete information systems; indiscernibility relation; limited tolerance relation; rough set theory; Computer science; Educational programs; Information systems; Knowledge acquisition; Probability; Set theory; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7280-8
Type :
conf
DOI :
10.1109/FUZZ.2002.1006657
Filename :
1006657
Link To Document :
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